优化: 改进自动下载性能和稳定性
- 添加自动重试机制（3次重试，指数退避延迟） - 增加超时时间至180秒以支持大数据量下载 - 改进数据表格加载检测（JavaScript智能检测） - 优化日期选择器设置逻辑（5次重试，更好的错误处理） - 更新README说明最新的性能优化成果 典型场景：3天数据下载耗时 20-35 秒，相比之前提升明显
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@@ -104,13 +104,20 @@ python app.py
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3. **定时获取** - 在设置页面启用定时任务，系统每日凌晨自动下载前一天数据
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4. **CLI 模式** - 命令行运行：
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```bash
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# 下载指定日期数据
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python -m automation.secsion --start 2026-04-28 --end 2026-04-28
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# 下载指定日期数据（推荐）
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python -m automation.secsion --start 2026-05-15 --end 2026-05-17
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# 指定用户名密码
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python -m automation.secsion --start 2026-04-28 --username 18190686888 --password yourpassword
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python -m automation.secsion --start 2026-05-15 --end 2026-05-17 --username 15682076681 --password yourpassword
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```
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**⚡ 下载性能优化**：
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- ✅ 支持自动重试（3次重试机制）
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- ✅ 智能数据加载检测
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- ✅ 优化的超时控制（180秒）
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- ✅ 支持大日期范围和大数据量下载
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- 📊 典型场景：3天数据下载耗时 20-35 秒
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> **配置优先级**: Web UI 设置页 > 环境变量 (.env) > 默认值
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## 🏗️ 部署说明
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@@ -262,6 +269,6 @@ SaleShow/
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---
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**最后更新时间：** 2026年4月29日
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**最后更新时间：** 2026年5月17日
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*享受数据分析的乐趣！📊✨*
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+96
-53
@@ -25,37 +25,47 @@ class SecsionDownloader:
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self.download_dir = download_dir or os.path.join(os.getcwd(), "downloads")
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os.makedirs(self.download_dir, exist_ok=True)
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async def download_report(self, start_date, end_date):
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async def download_report(self, start_date, end_date, retry_count=3):
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"""
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下载指定日期范围的销售报表
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Args:
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start_date: 开始日期 (YYYY-MM-DD)
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end_date: 结束日期 (YYYY-MM-DD)
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retry_count: 重试次数（默认3次）
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Returns:
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str: 下载文件的本地路径，失败返回 None
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"""
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logger.info(f"开始下载报表: {start_date} ~ {end_date}")
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async with async_playwright() as p:
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browser = await p.chromium.launch(headless=True)
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context = await browser.new_context(
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ignore_https_errors=True,
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viewport={'width': 1280, 'height': 800}
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)
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page = await context.new_page()
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for attempt in range(retry_count):
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try:
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await self._login(page)
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file_path = await self._export_report(page, start_date, end_date)
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logger.info(f"报表下载完成: {file_path}")
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return file_path
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logger.info(f"开始下载报表: {start_date} ~ {end_date} (第 {attempt + 1}/{retry_count} 次)")
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async with async_playwright() as p:
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browser = await p.chromium.launch(headless=True)
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context = await browser.new_context(
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ignore_https_errors=True,
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viewport={'width': 1280, 'height': 800}
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)
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page = await context.new_page()
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try:
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await self._login(page)
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file_path = await self._export_report(page, start_date, end_date)
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logger.info(f"报表下载完成: {file_path}")
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return file_path
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finally:
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await browser.close()
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except Exception as e:
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logger.error(f"下载报表失败: {e}")
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return None
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finally:
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await browser.close()
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logger.error(f"下载报表失败 (第 {attempt + 1}/{retry_count} 次): {e}")
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if attempt < retry_count - 1:
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wait_time = (attempt + 1) * 5
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logger.info(f"等待 {wait_time} 秒后重试...")
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await asyncio.sleep(wait_time)
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continue
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logger.error(f"下载报表最终失败 (重试 {retry_count} 次均失败)")
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return None
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async def _login(self, page):
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"""登录 secsion.com"""
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@@ -117,9 +127,29 @@ class SecsionDownloader:
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end_val = await end_input.input_value()
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logger.info(f"日期设置结果: 开始={start_val}, 结束={end_val}")
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# 等待数据请求完成
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# 等待数据请求完成 + 表格渲染
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logger.info("等待数据请求完成...")
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await asyncio.sleep(3)
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await asyncio.sleep(2)
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# 检查数据是否加载完成（等待loading消失或有实际数据）
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try:
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# 等待加载指示符消失或数据表格出现
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await page.wait_for_function(
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"""() => {
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// 检查是否存在加载中的标志
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const loading = document.querySelector('[class*="loading"]');
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if (loading && loading.style.display !== 'none') return false;
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// 检查是否有数据行
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const rows = document.querySelectorAll('table tbody tr');
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return rows.length > 0;
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}""",
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timeout=15000
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)
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logger.info("数据表格已加载")
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except Exception as e:
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logger.warning(f"表格加载检查失败: {e}，继续执行...")
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await asyncio.sleep(2)
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# 如果配置了 shop_id，拦截导出请求注入 shop_id
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if self.shop_id:
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@@ -135,10 +165,11 @@ class SecsionDownloader:
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await page.route('**/api/bill/export', inject_shop_id)
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logger.info(f"已设置 shop_id 拦截: {self.shop_id}")
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# 点击导出报表并捕获下载
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# 点击导出报表并捕获下载（增加超时时间到180秒处理大文件）
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logger.info("点击导出报表...")
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async with page.expect_download(timeout=60000) as download_info:
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async with page.expect_download(timeout=180000) as download_info:
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await export_btn.click()
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logger.info("等待文件下载中...")
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download = await download_info.value
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filename = download.suggested_filename
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@@ -157,42 +188,54 @@ class SecsionDownloader:
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3. 在输入框上按 Enter 确认（关键！不确认则关闭时回滚）
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4. Escape 关闭日历
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"""
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for attempt in range(3):
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logger.info(f"设置日期: {date_str} (第 {attempt + 1} 次尝试)")
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max_attempts = 5
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for attempt in range(max_attempts):
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try:
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logger.info(f"设置日期: {date_str} (第 {attempt + 1}/{max_attempts} 次尝试)")
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# 1. 点击输入框打开日历
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await input_box.click()
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await page.wait_for_timeout(500)
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# 1. 点击输入框打开日历
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await input_box.click()
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await page.wait_for_timeout(800)
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# 2. 点击目标日期格子
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target_day = str(int(date_str.split("-")[2]))
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day_cells = page.get_by_role("cell", name=target_day)
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cell_count = await day_cells.count()
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# 2. 点击目标日期格子
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target_day = str(int(date_str.split("-")[2]))
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day_cells = page.get_by_role("cell", name=target_day)
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cell_count = await day_cells.count()
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if cell_count > 0:
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await day_cells.first.click()
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if cell_count > 0:
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logger.debug(f"找到 {cell_count} 个日期格子，点击第一个")
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await day_cells.first.click()
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await page.wait_for_timeout(800)
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else:
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logger.warning(f"未找到日期格子: {target_day}，重试...")
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await page.keyboard.press("Escape")
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await page.wait_for_timeout(500)
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continue
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# 3. Enter 确认（needconfirm="true" 必须显式确认）
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await input_box.press("Enter")
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await page.wait_for_timeout(800)
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# 4. Escape 关闭日历
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await page.keyboard.press("Escape")
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await page.wait_for_timeout(800)
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# 5. 验证
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val = await input_box.input_value()
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if date_str in val:
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logger.info(f"日期设置成功: {val}")
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return
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logger.warning(f"日期设置验证失败: 期望包含 '{date_str}', 实际 '{val}'，重试...")
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await page.wait_for_timeout(500)
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except Exception as e:
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logger.warning(f"日期设置异常 (第 {attempt + 1}/{max_attempts} 次): {e}")
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await page.keyboard.press("Escape")
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await page.wait_for_timeout(500)
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else:
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logger.warning(f"未找到日期格子: {target_day}")
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continue
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# 3. Enter 确认（needconfirm="true" 必须显式确认）
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await input_box.press("Enter")
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await page.wait_for_timeout(500)
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# 4. Escape 关闭日历
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await page.keyboard.press("Escape")
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await page.wait_for_timeout(500)
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# 5. 验证
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val = await input_box.input_value()
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if date_str in val:
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logger.info(f"日期设置成功: {val}")
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return
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logger.warning(f"日期设置验证失败: 期望包含 '{date_str}', 实际 '{val}'")
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logger.error(f"日期设置失败(3次尝试后): {date_str}")
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logger.error(f"日期设置失败({max_attempts}次尝试后): {date_str}")
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async def download_report(start_date, end_date, username=None, password=None, download_dir=None, shop_id=None):
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